Measurement of Diaphragmatic Electrical Activity by Surface Electromyography in Intubated Subjects and Its Relationship With Inspiratory Effort
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Quantification of patient effort during spontaneous breathing is important to tailor ventilatory assistance. Because a correlation between inspiratory muscle pressure (P mus ) and electrical activity of the diaphragm (EA di ) has been described, we aimed to assess the reliability of surface electromyography (EMG) of the respiratory muscles for monitoring diaphragm electrical activity and subject effort during assisted ventilation. METHODS: At a general ICU of a single university-affiliated hospital, we enrolled subjects who were intubated and on pressure support ventilation (PSV) and were on mechanical ventilation for > 48 h. The subjects were studied at 3 levels of pressure support. Airway flow and pressure; esophageal pressure; EA di ; and surface EMG of the diaphragm (surface EA di ), intercostal, and sternocleidomastoid muscles were recorded. Respiratory cycles were sampled for off-line analysis. The P mus /EA di index (PEI) was calculated by relying on EA di and surface EA di (surface PEI) from an airway pressure drop during end-expiratory occlusions performed every minute. RESULTS: surface EA di well correlated with EA di and P mus , in particular, after averaging breaths into deciles (R = 0.92 and R = 0.84). When surface PEI was used with surface EA di , it provided a reliable estimation of P mus (R = 0.94 in comparison with measured P mus ). CONCLUSIONS: During assisted mechanical ventilation, EA di can be reliably monitored by both EA di and surface EMG. The measurement of P mus based on the calibration of EA di was also feasible by the use of surface EMG.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it